🛉 Reddit Data Cleanup & Sentiment Analysis

Welcome to the Reddit Data Cleanup & Sentiment Analysis repository!
This tool helps you analyze the sentiment of Reddit submissions provided in JSON format and outputs a single CSV file summarizing the results — all with a beginner-friendly setup.

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📁 Repository Structure

Reddit-Sentiment-Analysis/
├── input/                      # Folder containing input .json files (sample files included)
│   ├── sample1.json
│   └── sample2.json
├── sentimentAnalysis.py       # Python script to perform sentiment analysis
├── output.csv                 # Output CSV (auto-generated after running the script)
└── README.md                  # This file

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🔧 Features

• Accepts .json files of Reddit submissions placed inside the input/ folder.
• Performs sentiment analysis using NLTK's SentimentIntensityAnalyzer.
• Outputs a single output.csv summarizing sentiment scores per day.

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🚀 Getting Started

No prior experience? No worries — follow these steps to set up everything from scratch!

1. Clone the Repository

git clone https://github.com/VISHNUDAS-tunerlabs/Reddit-Sentiment-Analysis
cd reddit-data-cleanup

2. Set Up a Virtual Environment

It's recommended to use a virtual environment to manage dependencies:

# Create a virtual environment
python3 -m venv venv

# Activate the virtual environment
# On macOS/Linux:
source venv/bin/activate

# On Windows:
venv\Scripts\activate

3. Install Dependencies

pip install -r requirements.txt

If there's no requirements.txt, just run:

pip install nltk pandas

And don't forget to download NLTK resources:

# Run this in a Python shell
import nltk
nltk.download('vader_lexicon')

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▶️ Running the Script

Once everything is set up, simply run:

python sentimentAnalysis.py

This will:

• Read all .json files in the input/ folder.
• Perform sentiment analysis on each submission.
• Generate a single output.csv file in the root directory.

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📂 Sample Data

We've included a couple of sample .json files inside the input/ folder so you can test the script right away.

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📌 Notes

• Make sure your .json files contain a top-level field named submissions, where each item has a created_utc timestamp and body or text for sentiment analysis.
• The script assumes the timestamp is in UNIX format and converts it to daily aggregation.

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🤝 Contributing

Feel free to fork the repo and contribute via pull requests. Suggestions and improvements are always welcome!

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📬 Contact

Have questions or need help? Open an issue or reach out!